Abstract
Abstract Background/Aims Genome-wide association studies studies have identified many genetic variants associated with the risk of developing common rheumatological conditions. These variants primarily affect regulatory elements of the genome which can affect the expression of genes located far away from their genomic location through chromatin interaction mechanisms. Furthermore, common genetic variants have been associated with specific changes in chromatin interactions in cell lines. Studying chromatin interactions can improve our understanding of these diseases. Here, we aim to study chromatin interactions and how they are affected by genetic variation in primary immune cells that are relevant for rheumatological conditions. Methods We generated promoter Capture Hi-C (pCHi-C) data for primary CD4+ T cells and CD14+ monocytes isolated from peripheral blood of 10 systemic sclerosis patients and 5 healthy controls. We developed a new computational pipeline to explore how genetic variation affects chromatin interactions. Briefly, genotypes were called from the pCHi-C data using a modified GLIMPSE pipeline. Genotypes were phased using the integrated phasing pipeline which combined population haplotype information with the pCHi-C data. Reads were then assigned to the correct allele using SNPsplit and assigned to chromatin loops (CHiCAGO score > 5). A test for allelic imbalance was carried out using a binomial test, and results were consolidated using Fisher’s method. Results We identified 171 and 139 allele-associated loops (FDR < 0.05) in CD4+ T cells and CD14+ monocytes respectively. These interactions are cell-type specific and highly associated with expression quantitative trait loci (eQTLs). We found that 80% of the variants involved in allele-associated loops were eQTLs for at least one gene. These interactions link to the promoters of 62 and 57 distal genes in CD4+ T cells and CD14+ monocytes respectively. Of these, 38 and 31 respectively were also eQTL for those genes. Many of these allele-associated interactions affect genomic regions that are highly significant for the function of these cell populations. For example, a region with variants affecting T cell-specific chromatin interactions is the TRAF3IP3/IRF6/UTP25 locus. In this region there are separate groups of variants which affect gene expression with a complex mechanism. A group of variants overlapping the UTP25 promoter increases interaction strength with the TRAF3IP3 and IRF6 gene bodies. Interestingly, these are also associated with an increase in UTP25 expression but a decrease in TRAF3IP3 and IRF6 expression. Another group of variants located near the IRF6 promoter is associated with increased interactions with the UTP25 promoter. In contrast, these variants are associated with a reduction of UTP25 expression but an increase in TRAF3IP3 and IRF6 expression. Conclusion We created a new pipeline that allows the identification of allele-associated chromatin interactions in primary cells. These new data will be helpful in uncovering mechanisms of gene regulation in loci highly significant to autoimmune conditions. Disclosure D. González-Serna: None. C. Shi: None. M. Kerick: None. J. Hankinson: None. J. Ding: None. A. McGovern: None. M. Tutino: None. G. Villanueva Martin: None. N. Ortego-Centeno: None. J. Luis Callejas: None. J. Martin: None. G. Orozco: None.
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